In today’s Financial Industry, performance of application is one of the most critical aspects. Whether it is a banking application dealing with millions worth of transactions, balance transfers or trading application dealing with time sensitive trades and orders or...
In our previous blog on regression analysis, we have discussed how machine learning models can predict continuous outcomes, such as house prices or sales revenue, based on input data. While regression models are powerful, their success depends heavily on the quality...
Regression is one of the most important techniques in predictive modelling. It is usually the gateway into the world of data science and machine learning, offering a perfect balance of simplicity and power. Whether you're forecasting next month's sales figures or...
As artificial intelligence continues to expand, the importance of effectively communicating with large language models (LLMs) is crucial. Whether you are a data scientist, business user, AI developer, or engineer, structuring and contextualizing...
Assume that everyone is dressed casually at a party, except for one person who is wearing a superhero outfit. You notice that person right away since they do not fit in the crowd. This superhuman visitor is referred to as an outlier in data analysis. They could be...
As AI agents become increasingly prevalent in software applications, it's essential to ensure they're performing optimally. But how do you measure their success? The answer lies in evaluations (evals). In this post, we'll explore the importance of evals for...
Ever since OpenAI introduced ChatGPT UI in November 2022, the way we interact, process and consume information has changed drastically. It was science fiction to have a long and meaningful conversation with a machine until this point. ChatGPT, which is based...
In 2015, one of the largest e-commerce companies built an automated hiring tool to review and filter resumes based on skill sets and job descriptions. However, this project had to be halted after it was noticed that the hiring tool showed significant...
In our previous post, we introduced Linear Regression, a fundamental technique used to predict outcomes based on a single factor—such as estimating house prices based on square footage. We also discussed essential performance metrics like Mean Squared Error (MSE) and...
In today's data intensive world, data scientists play a crucial role. Their main job is to make sense of large amounts of data, turning it into useful information that can guide decisions. This involves both creative and technical skills, using a range of methods and...